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Improving Retail Digital Shopping Offerings

Rob Mason
Applause

Retailers continue to grapple with challenges wrought by the pandemic and its after effects: supply chain woes, difficulty staffing positions, surging inflation and more. And just as they had to do as a result of the pandemic, retailers continue to depend upon digital interactions to attract, maintain and retain consumers.

In fact, people around the world spent more than 100 billion hours in shopping apps in 2021, an 18% increase from 2020. While that eye-popping number is impressive enough on its own, it takes on even more significance when you consider that most of the world was locked down during the bulk of 2020. Yet even as restrictions were relaxed during 2021, people continued to turn to digital alternatives for their retail needs.

But shoppers expect a great deal from their digital retail interactions. Research shows that almost 90% of consumers will leave a trusted brand after only two unsatisfactory experiences, and 17% of consumers will abandon a purchase after just one negative experience. Moreover, half of consumers abandon apps after just one day, which not only hurts a retailer's app store rankings but also results in lost revenue.


But building strong customer relationships via digital channels is no simple task for retailers given the seemingly endless number of digital platforms, devices, payment methods and technologies available today. So how can today's retailers ensure their digital offerings overcome these challenges and attract and retain the valuable customers they desperately need?

According to The State of Digital Quality In Retail 2022, the answer is that retailers need testing strategies to ensure their digital retail experiences are seamless, easy to use, intuitive, inclusive and localized. Specifically, the report calls out a number of issues that are concerning for retailers, including:

Workflow errors are the most common flaw on retail sites

These functional errors account for almost 75% of all functional test bugs, with the overall result that consumers can't complete tasks they're attempting – things like adding things to the cart or accessing chatbots for assistance. Combating these issues requires retailers to research and develop test plans that take advantage of the valuable data they have about their customer, and those tests should be based on data from actual customers.

Accessibility has to be a primary focus and not an afterthought

The World Health Organization estimates that more than 1 billion people – or about 15% of the world's population – live with some form of disability. The report shows that 72% of all accessibility bugs relate to screen readers, which means customers can't navigate or discern what's on the page. Combating these types of issues requires retailers to utilize a variety of testing approaches to ensure customers can complete tasks, and those tests should be conducted by people with disabilities to ensure digital experiences are accessible to everyone.

Localization testing is vital for expansion into new markets

Shoppers want experiences in their local languages, yet 63% of bugs are related to poor and missing translations. Addressing localization errors requires retailers to validate translations in context with in-market speakers, and to research and understand cultural nuances.

Functional errors account for 89% of payment testing bugs

And those errors mean that orders and payments didn't go through for a number of reasons, including issues with particular payment instruments, merchants or capture devices. As such, retailers must focus on ensuring the payment methods most used by customers work properly, and include functionalities like refunds, promotional offers and discounts.

There's no question that digital retail interactions will continue to grow and evolve as people increasingly turn to devices for their shopping needs. Providing high-quality digital experiences is vital for retailers that want to attract and retain customers and protect their brand's reputation. By conducting comprehensive testing, retailers can identify ways to improve digital quality, and ensure better shopping experiences that are accessible to all.

Rob Mason is CTO of Applause

Hot Topics

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Improving Retail Digital Shopping Offerings

Rob Mason
Applause

Retailers continue to grapple with challenges wrought by the pandemic and its after effects: supply chain woes, difficulty staffing positions, surging inflation and more. And just as they had to do as a result of the pandemic, retailers continue to depend upon digital interactions to attract, maintain and retain consumers.

In fact, people around the world spent more than 100 billion hours in shopping apps in 2021, an 18% increase from 2020. While that eye-popping number is impressive enough on its own, it takes on even more significance when you consider that most of the world was locked down during the bulk of 2020. Yet even as restrictions were relaxed during 2021, people continued to turn to digital alternatives for their retail needs.

But shoppers expect a great deal from their digital retail interactions. Research shows that almost 90% of consumers will leave a trusted brand after only two unsatisfactory experiences, and 17% of consumers will abandon a purchase after just one negative experience. Moreover, half of consumers abandon apps after just one day, which not only hurts a retailer's app store rankings but also results in lost revenue.


But building strong customer relationships via digital channels is no simple task for retailers given the seemingly endless number of digital platforms, devices, payment methods and technologies available today. So how can today's retailers ensure their digital offerings overcome these challenges and attract and retain the valuable customers they desperately need?

According to The State of Digital Quality In Retail 2022, the answer is that retailers need testing strategies to ensure their digital retail experiences are seamless, easy to use, intuitive, inclusive and localized. Specifically, the report calls out a number of issues that are concerning for retailers, including:

Workflow errors are the most common flaw on retail sites

These functional errors account for almost 75% of all functional test bugs, with the overall result that consumers can't complete tasks they're attempting – things like adding things to the cart or accessing chatbots for assistance. Combating these issues requires retailers to research and develop test plans that take advantage of the valuable data they have about their customer, and those tests should be based on data from actual customers.

Accessibility has to be a primary focus and not an afterthought

The World Health Organization estimates that more than 1 billion people – or about 15% of the world's population – live with some form of disability. The report shows that 72% of all accessibility bugs relate to screen readers, which means customers can't navigate or discern what's on the page. Combating these types of issues requires retailers to utilize a variety of testing approaches to ensure customers can complete tasks, and those tests should be conducted by people with disabilities to ensure digital experiences are accessible to everyone.

Localization testing is vital for expansion into new markets

Shoppers want experiences in their local languages, yet 63% of bugs are related to poor and missing translations. Addressing localization errors requires retailers to validate translations in context with in-market speakers, and to research and understand cultural nuances.

Functional errors account for 89% of payment testing bugs

And those errors mean that orders and payments didn't go through for a number of reasons, including issues with particular payment instruments, merchants or capture devices. As such, retailers must focus on ensuring the payment methods most used by customers work properly, and include functionalities like refunds, promotional offers and discounts.

There's no question that digital retail interactions will continue to grow and evolve as people increasingly turn to devices for their shopping needs. Providing high-quality digital experiences is vital for retailers that want to attract and retain customers and protect their brand's reputation. By conducting comprehensive testing, retailers can identify ways to improve digital quality, and ensure better shopping experiences that are accessible to all.

Rob Mason is CTO of Applause

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.